I won't give you the clichéd line that it's never too late because that's not the point. It is actually because, a term that I loved as soon as I came across it- 'The AI Winter' - doesn't seem to ever be going to return again.

I am writing this article to show you the basics of using Instagram in a programmatic way. You can benefit from this if you want to use it in a data analysis, computer vision, or any other cool project you can think of.

This live webinar (Aug 22) will discuss the impact that the notebook experience has had on data science, and how JupyterLab - the next generation data science IDE - has evolved from the classic notebooks.

Boosted decision trees are responsible for more than half of the winning solutions in machine learning challenges hosted at Kaggle, and require minimal tuning. We evaluate two popular tree boosting software packages: XGBoost and LightGBM and draw 4 important lessons.

Whether you want to start learning deep learning for you career, to have a nice adventure (e.g. with detecting huggable objects) or to get insight into machines before they take over, this post is for you!

Until recently, deep learning alluded to the big names in tech such as Amazon, Facebook, and Google as having a clear use for these tools. Whilst these are some of the key players in AI and DL implementation, there are also huge advantages for their applications in businesses and everyday enterprises.

Every time DeepMind publishes a new paper, there is frenzied media coverage around it. We examine what is and is not real in recent work described as “DeepMind Neural Network Can Make Sense of Objects Around It”.

When used in combination with big data and machine learning, both AI and robotics can actively improve over time as they collect more information. You don’t have to look far to see how these technologies have revolutionized the world, and continue to do so.

Also: How I Used Deep Learning To Train A Chatbot To Talk Like Me; Making Predictive Models Robust: Holdout vs Cross-Validation; How Convolutional Neural Networks Accomplish Image Recognition?; Top Influencers for Data Science

The validation step helps you find the best parameters for your predictive model and prevent overfitting. We examine pros and cons of two popular validation strategies: the hold-out strategy and k-fold.

This blog introduces the basics of reinforcement learning. We are going to see how reinforcement learning might help us to address these challenges; to work smarter at the edge when brute force technology advances will not suffice.

This collection of concise introductory data science tutorials cover topics including the difference between data mining and statistics, supervised vs. unsupervised learning, and the types of patterns we can mine from data.

While earlier entrants in this series covered elementary classification algorithms, another (more advanced) machine learning algorithm which can be used for classification is Support Vector Machines (SVM).

Why can't you guys comment your f*cking code?; Train Chrome's Trex character to play independently; How to make a racist AI without really trying; Is training a NN to mimic a closed-source library legal?; 37 Reasons why your NN is not working

Until recently, deep learning alluded to the big names in tech such as Amazon, Facebook, and Google as having a clear use for these tools. Whilst these are some of the key players in AI and DL implementation, there are also huge advantages for their applications in businesses and everyday enterprises.

This post outlines the approach taken at a recent deep learning hackathon, hosted by YCombinator-backed startup DeepGram. The dataset: EEG readings from a Stanford research project that predicted which category of images their test subjects were viewing using linear discriminant analysis.

Join IAPA on 18 October in Melbourne to hear international experts share insights behind machine learning, data science and analytics; listen to local experts explain how they’ve used data to change their business. Get super early bird rates or become IAPA member and save even more.

Deep learning makes it possible to convert unstructured text to computable formats, incorporating semantic knowledge to train machine learning models. These digital data troves help us understand people on a new level.

Though it doesn’t get a lot of buzz, sampling is fundamental to any field of science. Marketing scientist Kevin Gray asks Dr. Stas Kolenikov, Senior Scientist at Abt Associates, what marketing researchers and data scientists most need to know about it.

In this post, we’ll be looking at how we can use a deep learning model to train a chatbot on my past social media conversations in hope of getting the chatbot to respond to messages the way that I would.

EDSF provides a conceptual basis for the Data Science Profession definition, targeted education and training, professional certification, organizational and individual skills management and career transferability.

AI and Analytics driven solutions have been widely adopted across different industries for various purposes. However, only a handful of banks around the world are working with advanced analytics and artificial intelligence technologies to improve their risk and compliance activities.

Compared to the state-of-art, DeepSense provides an estimator with far smaller tracking error on the car tracking problem, and outperforms state-of-the-art algorithms on the HHAR and biometric user identification tasks by a large margin.

Data Science expert Mikio Braun on the anatomy of an architecture to bring data science into production. Learn more at his talk at Strata NYC - Use code KDNU for additional 20% off (best price ends Aug 11).

Toolkits for standard neural network visualizations exist, along with tools for monitoring the training process, but are often tied to the deep learning framework. Could a general, easy-to-setup tool for generating standard visualizations provide a sanity check on the learning process?

Read this insightful interview with Bokeh's core developer, Bryan Van de Ven, and gain an understanding of what Bokeh is, when and why you should use it, and what makes Bryan a great fit for helming this project.